On-site analyzer

ABSTRACT

An apparatus ( 10 ) for analyzing lubricant oils and functional fluids includes an optical emission spectrometer (OES) ( 26 ) having a substantially continuously valued wavelength versus intensity output ( 140 ). The OES ( 26 ) analyzes light captured from a spark emission stand ( 58 ) through which the fluid sample is flowed. An expert system ( 160-172 ) operates according to a set of Rules that corrects background influence from the electrodes, and generates diagnostic text ( 174 ) for an operator based on the information about the fluid sample provided by the OES ( 26 ) and other measurement devices. The apparatus ( 10 ) is reduce in size, weight and cost.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims the benefit of U.S. provisional patentapplication serial No. 60/096,494 filed Aug. 14, 1998 which is herebyexpressly incorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

1. Technical Field

This invention relates generally to an apparatus and method foranalyzing a fluid sample, and, more particularly, to a self-containedanalyzer for on-site use and analysis.

2. Discussion of the Related Art

There has been much interest and investigation into apparatus andmethods for obtaining accurate analysis of lubricating oils (used andfresh) as well as functional fluids. The term “functional fluids”relates to liquid materials used in mechanical equipment, and which maybe or may perform primarily lubrication and/or power transmissionfunctions (e.g., gearbox oils, automatic transmission fluid, machineoils and hydraulic fluids or oils, etc.). “Functional fluids” alsoincludes coolants, thermal transmission media, and fuels. The reasonsfor such interest include, but are not limited to, (i) the assessment ofthe constituent, condition and quality of the oil/fluid, (ii) thecondition of the equipment from which the oil/fluid was drawn, and (iii)the condition of components of such equipment.

As is known, oil is generally used to lubricate moving parts inmechanical systems, such as engines, transmissions, hydraulics andvehicles. Certain substances, referred to generally as contaminants, arenot originally present in the oil but rather are produced as theby-products of wear and corrosion. For example, metal particulates maybe formed through abrasion or chemical corrosion and cause furtherdeterioration of internal parts. In addition, normal operation causesoxidation, nitration and sulfation of the oil, altering a desiredchemistry thereof. Further, leaks between the cooling systems and thelubricating system may cause coolant (mixtures of water, ethylene glycoland other coolant chemicals) to be introduced into the oil.

Lubricant oil filters are designed to remove the larger sizeparticulates from oil. However, this gross filtering nonetheless leavesthe majority of smaller contaminants free to further affect theequipment. For example, non-metallic components, such as pumpdiaphragms, gaskets and seals, fluid lines and the like, may be furtheraffected. Moreover, contaminants in the oil, such as ethylene glycol,fuel, silicone, water, soot and other chemicals may also presentconcerns.

Historically, accurate oil analysis has been provided mainly in alaboratory setting, such as, for example, a system utilized in alaboratory as disclosed in U.S. Pat. No. 3,526,127 issued to Sarkis onSep. 1, 1970.

One approach to accurate on-site oil analysis was to provide aself-contained test assembly in a single housing, as described in U.S.Pat. Nos. 5,517,427 and 5,537,336, both issued to Joyce (the “Joycepatents”), both hereby expressly incorporated by reference in itsentirety. The Joyce patents disclose a test assembly that includes aninfrared (IR) spectrometer and an optical emission spectrometer forproducing a report on the amount of certain metals in an oil sample,other oil contaminants such as water, glycol, soot, etc. as well as oilcondition. With respect to the optical emission spectrometer portion,the Joyce patents disclose the use of “photocells” (the commercialembodiment corresponding to the Joyce patents employed well-known photomultiplier tubes (PMT)) to optically monitor spark induced lightemissions of the oil sample to determine wear metals content.

Although PMTs in the manner configured (i.e., incorporated into a largemonochromator in the commercial embodiment corresponding to the Joycepatents) provide “high resolution”, such a configurations presentscertain constraints. First, inherent in such systems are certaingeometric and mechanical constraints imposed by the physical dimensionsof a PMT. Since each PMT was configured to monitor a fixed wavelength,the system had to be made relatively, physically large to ensure thatlight from multiple wavelengths would not impinge on the same PMT.Second, the configuration provided little if any flexibility in emissionline selection/reconfiguration. Finally, as the number of monitoredemission lines increased, so would the corresponding cost (due to therequired addition of another PMT). Thus, while the apparatus disclosedin the Joyce patents provided satisfactory performance, it would bedesirable to provide an apparatus having a reduced size, weight andcost.

Accordingly, there is a need to provide an improved apparatus foranalysis of a fluid sample that minimizes or eliminates one or more ofthe problems as set forth above.

SUMMARY OF THE INVENTION

One object of the present invention is to provide an apparatus foranalyzing a fluid sample having a reduced size, weight and cost.

It is a further object to provide such an apparatus configurable foranalyzing and characterizing liquid lubricants as well as functionalfluids (e.g., hydraulic oils, etc.).

It is yet a further object of the present invention to provide such anapparatus that is highly customizable, and which can be reconfigured todetect and analyze desired, alternate elements.

To achieve these and other objectives, according to one aspect of thepresent invention, an apparatus for analyzing a fluid sample todetermine constituents thereof is provided. The apparatus includes five(5) major parts: a housing, a fluid transfer assembly, an infrared (IR)spectrometer assembly, an optical emission spectrometer (OES) assembly,and a computer controller.

The fluid transfer assembly includes an inlet configured to receive thefluid sample and is configured to selectively flow the fluid sample toan outlet thereof. The IR spectrometer assembly is disposed in thehousing, coupled to the outlet, and is configured to analyze the fluidsample and generate a first data set. In a constructed embodiment, theIR spectrometer comprises a Fourier Transform Infrared (FTIR)spectrometer. The OES assembly is also disposed in the housing, coupledto the outlet, and is configured to analyze the fluid sample andgenerate a second data set. The second data set is substantiallycontinuously valued over a first predetermined wavelength range.Finally, the computer controller is connected to the transfer assembly,the IR spectrometer assembly, and the OES assembly and is configured tocontrol the operation of the apparatus in accordance with apredetermined operating strategy. The computer controller is furtherconfigured to determine constituents of the fluid sample in accordancewith the first and second data sets.

In a preferred embodiment, the OES assembly includes a fluid sampleexcitation assembly, such as a spark emission assembly that includeselectrodes. The spark assembly is configured to excite the fluid sampleto spectroemissive levels to thereby generate radiation characteristicof the constituents in the fluid sample. The OES assembly furtherincludes a first spectrometer configured to receive the radiation andgenerate a first spectral pattern, and a second spectrometer configuredto receive the radiation and generate a second spectral pattern. Also inthe preferred embodiment, the first spectrometer has a first resolution,and the second spectrometer has a second resolution less than the firstresolution, which preferably may be 0.3 nm (half-width at half-height),and 1.0 nm (half-width at half-height), respectively.

In another aspect of the invention, the IR spectral analyzer assembly isconfigured to include an inventive flow cell assembly which minimizesthe undesirable effects of fringing. “Fringing” is manifested as asinusoidal feature in the intensity-versus-wavelength final spectrum,which interferes with the measurement of oil constituents. The IRspectral analyzer assembly includes an IR source, the flow cellassembly, and a detector assembly. The IR source is configured togenerate an IR radiation beam focused along a principal axis to convergeat the detector. The detector assembly is spaced apart from the IRsource. The flow cell assembly includes a sample cell and a compensatorwindow, and is slidably movable along a motion axis transverse to theprincipal axis. The flow cell assembly moves between a first positionwherein the compensator window is optically intermediate the IR sourceand the detector, and a second position wherein the sample cell isoptically intermediate the IR source and the detector.

The compensator window and the sample cell are each arranged such that arespective normal axis associated therewith define a predetermined tiltangle, preferably between about 20-25 degrees relative to the principalaxis. Moreover, in a preferred embodiment, the compensator window andthe sample cell each have an effective thickness and index of refractionthat are substantially equal. The foregoing insures that the focusedimages of the sample (i.e., through the sample cell), and the background(i.e., through the compensator window) coincide on the detector.

In yet another aspect of the present invention, a method is provided foradjusting the wavelength axis of a sample spectrum of a fluid samplegenerated by a spectrometer having a pair of electrodes.

The foregoing permits the use of low resolution optical emissionspectrometers to identify and quantitate elements, contaminants, andadditives of interest in fluid samples.

BRIEF DESCRIPTION OF THE DRAWINGS

Other features, advantages, and uses of the present invention will bereadily appreciated by one of ordinary skill in the art by reference tothe following detailed description when considered in connection withthe accompanying drawings, a brief description of which is set forthimmediately hereinafter.

FIG. 1 is a perspective view of an apparatus for analyzing a fluidsample in accordance with the present invention;

FIG. 2 is a perspective view of the apparatus shown in FIG. 1 having ahousing portion in an open position;

FIG. 3 is a simplified schematic and functional block diagram view ofthe apparatus of FIG. 1;

FIG. 4 is a simplified block diagram view of a power distribution schemaused in the apparatus of FIG. 1;

FIG. 5 is a simplified plan view showing, in greater detail, a keyboardportion of the apparatus of FIG. 1;

FIG. 6 is a simplified view illustrating, in greater detail, a screendisplay of the apparatus of FIG. 1;

FIG. 7 is a simplified schematic and block diagram view showing, ingreater detail, the FTIR assembly shown in block form in FIG. 3;

FIG. 8A is a simplified cross-sectional view of a first embodiment ofthe flow cell assembly shown in block form in FIG. 7;

FIG. 8B is a simplified, cross-sectional view of a preferred embodimentof the flow cell assembly shown in block form in FIG. 7;

FIG. 8C is a simplified, top view, relative to the orientationillustrated in FIG. 8B, of the preferred flow cell embodiment;

FIG. 8D is a simplified perspective view of an optical plate of a samplecell portion of the flow cell assembly shown in FIG. 8B;

FIG. 8E is a simplified, cross-sectional view of the optical plate FIG.8D, taken substantially along lines 8E—8E;

FIG. 9 is a block diagram view of the FTIR assembly shown in FIG. 7;

FIG. 10 is a diagrammatic and block diagram view showing, in greaterdetail, the optical emission spectrometer of FIG. 3;

FIG. 11 is a wavelength-versus-intensity spectral pattern illustratingintensity variation for the OES;

FIG. 12 is the spectral pattern of FIG. 11 at the red end about anemission line suitable for intensity normalization;

FIGS. 13A-13B illustrate a typical wavelength-versus-intensity spectralpattern for the OES for a reference base oil without and with anadditive;

FIG. 14 illustrates a reference oil with multiple additives;

FIGS. 15A-15C illustrate emission spectra for various new oils;

FIG. 16 is a simplified flow chart diagram of the operation of an expertsystem portion of the apparatus of FIG. 1;

FIG. 17 shows a sample output report generated by the apparatus of FIG.1;

FIG. 18 is a flowchart diagram of a method of regularizing a samplespectrum; and,

FIG. 19 is a flowchart diagram of a method of normalizing an intensityof a sample spectrum.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Referring now to the drawings wherein like reference numerals are usedto identify identical components in the various views, FIG. 1 shows, inperspective form, an apparatus 10 for analyzing a fluid sample 12 todetermine constituents thereof. “Constituents” may refer to (i)additives introduced into the fluid by design, (ii) wear metals (such asaluminum, chromium, copper, iron, lead, and tin), and (iii) contaminantsand fluid condition/degradation, which should be understood to includesnot only unexpected or undesired substances, but also changes in thefluid resulting from aging, usage, leakage of fluid from elsewhere intothe fluid sample, and the like (e.g., H₂O, glycol, fuel, soot,oxidation, nitration, sulfation, estimated viscosity, Total Base Number(TBN), and the like). Additionally, an extended set of detectableelements may include: Ag, Al, B, Ba, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Mo,Na, Ni, P, Pb, Si, Sn, Ti, V, and Zn. Note that detection of Ag mayrequire a changes in the electrode set when the electrodes used aresilver, as in a constructed embodiment.

Apparatus 10 is particularly suited for on-site measurement of used andfresh lubricating oils (e.g., motor oils) and functional fluids for theassessment of equipment condition and lubricant (functional fluidcondition and quality). The term “equipment” herein may relate tointernal combustion engines (two-cycle and four-cycle, diesel, gasolineor natural gas fired, or an alternate fuel-propelled engine),transmissions (manual and automatic), gearboxes, rear axles anddifferentials, turbines, and/or any other piece of rotating and/orreciprocating component which may be lubricated by a minimal orpartial-loss lubricant system.

While, in a preferred embodiment, apparatus 10 is specifically adaptedfor automotive applications, apparatus 10 may easily be adapted so as toextend to any powered lubrication system, including industrial,off-highway, stationary, locomotive, marine, aviation, miliary, andpower generation systems.

Moreover, while, in a preferred embodiment, apparatus 10 is illustratedand described for analyzing used lubricating oils, apparatus 10 may beextended for use in the characterization and quality assessment offresh, unused oil products (i.e., may be used for production controlapplications, such as at a refinery site).

An apparatus in accordance with the present invention provides anautomated, integrated apparatus for the measurement of oil/lubricantcondition, including the presence of key contaminants, as well as theassessment of equipment (and components thereof) from which the fluidsample 12 was drawn. The apparatus provides diagnostic information(exemplary report shown in FIG. 17) from an expert system portionthereof, based on operator-input data, measured sample data, andpredetermined data, for many equipment types. Two main technologies areincluded to determine sample constituent analysis: (i) optical emissionspectroscopy technology, and (ii) infrared (IR) spectroscopy technology.In one embodiment, certain standard analyses, such as viscosity, aredetermined indirectly based on a known spectral response for variousstandard oil and contamination. In alternate embodiments, where moreaccurate viscosity measurements are desirable, the apparatus may includea viscometer.

Referring to FIGS. 1 and 2, apparatus 10 includes a 2-tier “clam-shell”housing 14, an integrated keypad 16, a display 18, and an integratedfluid transfer assembly 20 having a sipper inlet 22, an infrared (IR)spectral analyzer system, such as Fourier Transform Infrared (FTIR)spectrometer system 24, a low resolution optical emission spectrometer(OES) assembly 26, a computer controller 28, and, optionally, aviscometer 30 and/or similar measuring apparatus like a densitometer.FIG. 1 shows housing 14 in a closed position. In a constructedembodiment, apparatus 10 may be about 965 mm (38 inches) Wide by 559 mm(22 inches) in Depth by 432 mm (17 inches) in Height (521 mm (20.5inches) in Height at display). In such a constructed embodiment,apparatus 10 may weigh about 67 Kg (150 lbs.).

FIG. 2 shows a “bench-top” embodiment of apparatus 10 with housing 14 inan open position. In an alternate embodiment, apparatus 10 may take theform of a stand alone embodiment on a movable custom-designed cart (notshown). Further alternate embodiments contemplated include arack-mounted embodiment, an environmentally protected embodiment (NEMAenclosure), and a transportable/portable embodiment. The ability tochange the form of apparatus 10 flows from the modularity of thehardware and software. In contrast, in previous (high resolution)analyzers employing photo multiplier tubes (PMTs) and largemonochromators were constrained by geometrical considerations.

FIG. 2 illustrates the modular approach to hardware configuration andother mechanical features of apparatus 10. Housing 14 includes a baseportion 32, an upper portion 34, a pivot 36, a rear access panel/opening38, and a shelf 40. An inner bottom surface of base portion 32 providesa first, lower tier, while shelf 40 provides a second, upper tier. Inthe open position (as illustrated in FIG. 2), housing 14 provides easyaccess to many of the functional components. Many of the power suppliesare disposed on shelf 40, adjacent a plurality of heat extraction fans(not shown), thereby providing rapid removal of heat generated by thesupplies. Further, housing 14 has been engineered to help comply with CErequirements—minimal radiation and emissions, plus immunity to externalelectrical or radiative interference. The ease of access to the internallocation of apparatus 10, when housing 14 is in the open position, easesassembly of apparatus 10. In addition, all removable surfaces and coversare protected by interlocks, preventing exposure to high voltagecomponents (i.e., the main line voltage is disconnected when theinterlocks are activated).

Housing 14 further includes means (not shown) for isolating apparatus 10from external vibrations, especially for the optical components. In aconstructed embodiment, four (one of which includes height adjustment)shock-absorbing feet are provided to define a first level of vibrationisolation. Apparatus 10 further includes a second level of vibrationisolation, namely, direct shock-mounts on the individual opticalcomponents (not shown).

Fluid transfer assembly 20 is provided for receiving a fluid sample 12at inlet 22 (FIG. 1), and flowing the sample concurrently, under controlof computer controller 28, to the various measurement instruments inapparatus 10. Transfer assembly 20 comprises a sampling region 42, oneor more sample distribution components designated generally atphantom-line box 44, a sample distribution power supply 46, a wastereceptacle region 48, and a flushing medium (fluid) reservoir 50. Wastereceptacle region 48 is adapted in size and configuration to receive awaste tray (not shown) to receive analyzed oil/fluid from apparatus 10.A level sensor is further provided (not shown) to alert an operator ofapparatus 10 when the waste tray needs to be emptied.

The fluid used for flushing apparatus 10 may comprise conventional andwell-known materials, and may comprise thin hydrocarbon material. In aconstructive embodiment, a citrus-based product, commercially availableunder the brand name “ELECTRON”, was satisfactorily used, available fromEcolink, Inc., a subsidiary of Sentry Chemical Company, Stone Mountain,Ga.

In the illustrative embodiment, FTIR spectrometer system 24 includes,from a packaging viewpoint, a FTIR power supply 52, and a FTIRoptics/control modular assembly 54.

In the illustrative embodiment, low resolution OES assembly 26 includes,from a packaging viewpoint, a spark source power supply 56, a sparkstand enclosure 58, and a spectrometer portion 60 (diagrammaticallyillustrated in FIG. 10).

In a constructed embodiment, computer controller 28, is packaged toinclude a passive backplane incorporating a single board processor ofthe type equipped with all conventional forms of input/output (I/O) anddevice interfaces, such as for disk drives, graphics, and the like. Eachof the measurement systems described herein communicate to computercontroller 28 by way of a dedicated, custom interface board located onthe passive backplane, or by way of a standard interface, such as anRS-232 serial port or a PC-104 interface. The computer controller 28controls, and communicates with, the other subsystem and apparatus 10.

In the illustrative embodiment, apparatus 10 may include an in-lineviscometer 30.

FIG. 3 shows a simplified functional block diagram of portions ofapparatus 10. FIG. 3 further shows a printer 62, a communicationsinterface 64, optionally, one or more other integrated analyzers 65(shown in phantom line), and an I/O interface 66.

Keyboard 16 is connected to computer controller 28 and is providedgenerally to enable an operator to command predetermined functions, suchas analyze, start, stop, and the like be performed. Keyboard 16functions as a control panel for the apparatus 10.

Display 18 provides a visual user interface and is linked to thesoftware component of the user interface executing on computercontroller 28.

Transfer assembly 20 is configured to receive a fluid sample 12, and toselectively flow the fluid sample, under the control of computercontroller 28, to an outlet 67 thereof. In a preferred embodiment,transfer assembly 20 includes a first multi-way valve, such as three-wayvalve 68, a second multi-way valve, such as 4-way valve 70, and a pump72. Transfer assembly 20 avoids the need for use of a manifold. Use ofmulti-way valves reduces the space occupied by the transfer system, aswell as the overall number of components needed for multi-directionalfluid sample transfer and distribution. The pump 72, also under controlof computer controller 28, is utilized for drawing in and distributingthe fluid sample, air entrainment (for fluid sample removal) and forsample flushing by cleansing or flush medium 50. In particular, computercontroller 28 controls both the speed and direction of pump 72. In aconstructed embodiment, the speed and direction are user programmable.Transfer assembly 20, under the control of computer controller 28, isoperative to perform following operations including but not limited to:fluid sample introduction, fluid sample direction to FTIR 24, OES 26, towaste receptacle 48, back-flushing (in the event of blockage), andcleansing. Apparatus 10 further includes a back pressuresensing/pressure relief valve 74 to protect the FTIR flow cell, therebyreducing the risk of cell fracture and/or leakage.

Infrared spectrometer, such as FTIR spectrometer system 24, is providedgenerally for optically testing the fluid sample 12 in generating afirst data set in response thereto. FTIR spectrometer system 24 isconnected to computer controller 28, and is controlled thereby. FTIR 24further includes an inlet coupled to outlet 67 of the fluid transfersystem. The FTIR spectrometer system 24 generally provides for measuringoil contaminants and wear products (physical parameters) in sample 12,such as oxidation, nitration, sulfation, fuel, water, glycol and soot.FTIR spectrometer system 24 may comprise conventional apparatus known inthe art such as that provided by FTIR manufacturers such as Midac,Bomem, Designs & Prototypes, Analect, Nicolet, Mattson, Bruker, PerkinElmer, and BioRad. FTIR spectrometer system 24 produces an infraredspectrum of the sample 12 indicative of light absorption by sample 12 atdifferent infrared frequencies, as generally known in the art. Empiricalcorrelations translate intensity-versus-frequency (or wavelength)information to physical parameter values. Upon completion of ananalysis, FTIR 24 provides computer controller 28 with theabove-mentioned output data.

OES assembly 26 is coupled to outlet 67 to receive a portion of thefluid sample 12, and is configured to analyze the fluid sample andgenerate a second data set. The second data set preferably comprises anarray of pixel values representative of spectral intensities inwavelength increments over a spectral range (i.e., is substantiallycontinuously valued over at least a first predetermined wavelengthrange, or, for any particular spectrometer, overall of its range). OESassembly 26 generally tests for and measures wear metals, contaminantelements, and additive elements found in fluid sample 12. OES assembly26 may comprise conventional and well-known apparatus commerciallyavailable in the art, such as available from CVI Laser and ControlDevelopment. In a constructed embodiment, OES 26 comprises acommercially available optical spectrometer, designated model SD2000,from Ocean Optics, Inc., 380 Main Street, Dunedin, Fla. 34698. OESassembly 26 is connected to and operates under the control of computercontroller 28. The above-mentioned second data set is provided by OES 26to computer controller 28 for subsequent analysis (e.g., determining“parts per million” of one or more constituent elements).

Computer controller 28 controls all functions of apparatus 10, providinghardware control, system diagnostics, user interface, databasemanagement, and data handling. Controller 28 in a preferred embodimentincludes an open-architecture type system software, such as Windows 98system software, commercially available from Microsoft, Redmond, Wash.As such, the environment is adapted for end-user customization forspecific applications. The software which computer controller 28executes is multi-layer in architecture, which is highly modular indesign and highly customizable. “Methods” (i.e., organization orsequencing a functional operation) development has been reduced to asimple point-and-click function, and this includes sequencing of allfunctional operations such as valve switching, spark ignition, dataacquisition (from any of the monitoring devices such as FTIR 24, and/orOES assembly 26), etc. Display and reporting functions are also easilycustomized to permit redesign of the user interface and the output ofresults. End-users may, in some embodiments, select the metals to beanalyzed and the physical/chemical analyses to be included as output inthe final report. For example, the end-user may select the foregoingfrom a list of available elements/tests.

In addition, computer controller 28 is programmed to provide a “Rules”editor for the expert system (to be described in further detailhereinafter) to enable straightforward updates thereto to satisfy therequirements and/or desires of specific markets and/or end-userapplications.

Another added feature of the software involves automatic diagnosticsthat provide constant feedback to the operator in the form of statuslights that indicate the condition and/or state of all functionalcomponents. A green status light indicates that a functional componentis operating correctly. If the status changes, but the changingcondition is not detrimental to the performance of apparatus 10, thespecific status light turns the color yellow. In the event that a faultoccurs, or a component fails to operate correctly, or if a disallowedoperation is performed (such as the upper portion of housing 14 israised by the operator while the power is on) the relevant statuslight(s) changes to the color red. A system diagnostics button shown ondisplay 18 allows the operator to review the status of all components,and to receive information about any change in status, malfunction orfailure. All main functional components provide some form of statusinformation each time they are addressed and/or operated.

Viscometer 30 may be included to provide a direct measure of a viscosityvalue of fluid sample 12. Viscometer 30 is logically connected to andoperates under the control of computer controller 28. Viscometer isphysically coupled in-line to outlet 67 of the transfer assembly toreceive a portion of fluid sample 12. Viscometer 30 is provided as anintegrated unit with a viscometer sensor and a thermal control jacketfor critical thermal control to a preset temperature. The viscometermeasurement cavity is designed to provide efficient flush-out, ensuringsample turn-around within 1-3 minutes (for up to 90 weight oils). Asingle electronics interface board provides viscometer control, thermalcontrol of the measurement head, signal handling and processing, andcommunications via a serial interface. For purposes of example only, anexemplary measuring range provided by viscometer 30 may be between about5 to 100 centipoise (cP), at 100° centigrade.

Printer 62 may comprise conventional and well-known apparatus. Printer62 is provided in connection with apparatus 10 for producing hard-copyoutput, such as producing an analysis reports for operators and/orend-user customers.

Communication interface 64 is provided for remote communications withapparatus 10. Communication interface 64 may comprise a conventionalfax/modem for remote communications, or, in an alternate embodiment,comprise a conventional Ethernet interface. Apparatus 10 may beinterrogated remotely for both operations and diagnostics, as well asfor assessment of usage (e.g., for billing purposes).

In an embodiment using a standard fax/modem, communication betweenapparatus 10 (near end) and a far end device may be two-way. A firstoption involves apparatus 10 faxing analysis results, billinginformation or diagnostic data to a predetermined fax telephone number.This feature of the invention enables an end-user to transmit resultsdirectly to a client or a central office (for example), to send billinginformation to an assigned agent, or to send diagnostic data, inparticular in the event of a component malfunction to a service bureau.A second option involves remote control wherein modem communicationfunctionality provide remote access to control apparatus 10, acquiredata, process results, as well as conduct system diagnostics.

In an embodiment incorporating an Ethernet network interface (or anyother conventional network interface), the apparatus 10 forms a portionof a centralized or decentralized network. For example, an optionalworkstation (not shown) may be connected through network facilities tocommunications interface 64, and thence to the control systemestablished by the software of apparatus 10. This network configurationoffers several advantages, particularly to an end-user. The advantagesof this configuration include: (1) allowing the end-user to pre-entersample information remotely, via a standard computer; (2) enabling anend-user to customize apparatus 10, and to extend the reportingabilities thereof; (3) providing the ability to produce trendinformation, with statistical evaluation of the results; and, (4)providing an access to external networks (LANS, WANS, and remotenetworks).

Block 65, if included, may comprise alternate measuring devices orinstruments (e.g., resistivity measuring device, densitometer, etc.).

I/O 66 may provide for the connection of, for example, a conventionalexternal keyboard and mouse for the set up phase of apparatus 10, forcarrying out service work, and/or for carrying out more extensivediagnostics. In addition, I/O 66 may provide an interface to a bar-codereader.

FIG. 4 illustrates a power distribution system included in apparatus 10which comprises a line conditioning device 76, and one or more powerinterlocks 78. Line conditioning device 76 protects apparatus 10 fromvoltage transients occurring on the input line. Certain covers,surfaces, and the like within housing 14 are protected by interlocks.The interlocks, when activated (e.g., by opening a cover), are operativeto either defeat operation of the protected subsystem (e.g., preventspark events from occurring in the spark stand) or remove power thereto.Each subsystem (as shown in FIG. 4) includes its own power supply, whichuses the input line voltage. Accordingly, due to the power supplyredundancy feature, failure of one power supply should not significantlyeffect operation of the other subsystem.

FIG. 5 shows keypad 16 in greater detail. As illustrated, keypad 16provides all of the options and functions of a regular computer keyboardbut, in addition, includes dedicated keys to initiate functionsavailable on apparatus 10. Keypad 16 provides a more intuitive interfaceand minimizes keystrokes, thereby speeding up data entry. For example,as shown, there is a dedicated “GASOLINE” key for use in connection withgasoline engine vehicles.

In addition, certain ones of the keys are color coded wherein the colorcoding is linked to the color of the key representation on the systemdisplay 18. For example, the following keys are rendered in the colororange: “STOP”, “PREVIOUS”, “NO”, and “CANCEL”. The following keys arerendered in blue: “FLUSH”, “STANDARDIZE”, “ANALYZE”, “HELP”, “PRINT”,“GASOLINE”, “DIESEL”, “TRANSMISSION”, “OTHER”, “USER”, “REPORT”, and theup, down, left, and right arrow keys. The “SHUTDOWN SYSTEM” key isrendered in the color red. The following keys are rendered in the colorgreen: “START”, “NEXT”, “YES”, “OKAY”, and “ENTER”. The remaining keysare rendered in one of two shades of grey. In a contemplated embodiment,keypad 16 may be implemented as a touch screen for preselected keyfunctions.

FIG. 6 shows screen display 18 in greater detail. In a constructedembodiment, display 18 comprises a bright TFT (active matrix) styledisplay.

Referring now to FIG. 7, IR spectrometer assembly, such as FTIRspectrometer system 24, includes, in addition to FTIR power supply 52,and FTIR optics/control module assembly 54, an FTIR interface card 80generating one or more control signals designated S₁, and a serviceslider arrangement 82.

Interface card 80, in a constructed embodiment, may be mechanicallyseated in the passive back plane referred to above, and as indicated inthe dashed-line box in FIG. 7 designated “PBP”. Service sliders 82 allowthe assembly 54 to be moved for, among other things, service.

Optics and control module 54 includes an infrared (IR) light source,such as an IR source 84, which provides a modulated source of IRradiation, lens 86 (best shown in FIG. 9), a detector assembly 88comprising a focusing mirror 90 and an IR detector 92 (best shown inFIG. 9), a flow cell assembly 94, and lateral translation means 96 formoving flow cell assembly 94 between first and second positions along amotion axis designated “M”.

As best shown in FIG. 9, IR source 84 is configured, by way of lens 86,to generate an infrared (IR) radiation beam focused along a principalaxis to converge. The envelope of the IR radiation beam is identified bythe dashed line in FIG. 9, while the principal axis is designated as“P”. The detector assembly 88 is spaced apart from the IR source 84. Ina preferred embodiment, lens 86 comprises zinc selenide material,includes a Broad Band anti-reflection (BBAR) coating, and has arelatively small focal length lens. The use of zinc selenide materialfor lens 86 (as well as for the flow cell optical components) improvesresistance to attack from atmospheric moisture, thereby enablingapparatus 10 to be used in relatively humid environments. Significantly,the use of a short focal length lens minimizes the free air spacebetween the main interferometer housing (i.e., the IR source housing),the flow cell assembly 94 and detector assembly 88, which, in aconstructed embodiment, typically extends no more than about 1″ (2.5centimeters). This short free air space in turn reduces spectralinterferences from water vapor. In addition, an important distance forreducing space is the distance from the IR source lens 86 to thedetector assembly 88, and may be about 3.5″ in a constructed embodiment.

Focusing mirror 90 may comprise conventional well-known apparatuscommercially available in the art.

Detector 92 may comprise conventional detector apparatus known in theart, and may comprise a TGS detector 92. In a constructed embodiment,TGS detector 92 comprises a 1.3 millimeter target size detector elementfor improved sensitivity (signal-to-noise).

Flow cell assembly 94 is translatable along motion axis “M”, whichextends transversely of principal axis “P”, by way of lateraltranslation means 96.

Lateral translation means 96 may comprise conventional and well-knownstructure available in the art, and is connected to and under control ofcomputer controller 28. Lateral translation means 96 is provided forautomated collection of instrument background data, which may be aunique, potentially time-variant characteristic of FTIR system 24. Thatis, flow cell assembly may periodically be moved to a first positionwherein the compensator window is intermediate, and preferably alignedto, the IR source and the detector, and wherein reference measurementsmay be taken.

In accordance with another aspect of the present invention, an inventiveflow cell assembly 94 is provided which reduces or minimizes theundesired effects of “fringing” (to be described hereinafter). Asbackground, typically, infrared transmission or flow cells are placed ina zone where the IR radiation is collimated. Light emerging from theinterferometer of a Fourier Transform Infrared spectrometer may alreadybe parallel and used for illuminating the optical cell containing thesample for study. The lens can then focus the light from the absorptionregion and refocus it onto a detector. The detector may includeadditional optics, but this added structure only enhances the ability ofthe system to image the infrared absorption zone of the cell on to thedetector.

The problem of fringing may be encountered when well-polished plane,parallel surfaces are at normal incidence to the IR beam. Conventionalflow cells have a sandwich-like structure: a pair of IR transmissiveplates between which is disposed a spacer which is usually the volumeoccupied by the sample. Light is reflected at every transition. If thedistance, as measured in optical terms (i.e., including the effects ofthe index of refraction of the absorption medium) is about equal to anintegral number of half-wavelengths of the incident light, a situationknown as “standing waves” will occur. Standing waves lead to acharacteristic sinusoidal “fringe pattern” which is imposed on to theactual signal being measured. The process of multiple reflections at thecorresponding multiple optical interfaces will be reinforced at theresonance wavelengths (or the corresponding frequencies) determined bythe spacing. For a distance of D cm spacing, with an index of refractionof the sample of n, the period in wavenumber units is: 1/(2 Dn) cm⁻¹.Thus, for a 0.1 mm cell (i.e., spacer thickness), the period is 50/ncm⁻¹. For indices of refraction ranging from 1 to 2, the fringe spacingis between about 25 to 50 cm⁻¹. This fluctuating signal may becomparable to the width of desired spectral features. The fringinginterference is therefore an undesirable artifact.

In accordance with the invention, a tilt angle is built into the flowcell assembly 94 so that incident light beams are reflected in adirection out of the optical path.

FIG. 8A shows a first flow cell assembly embodiment showing the built-intilt angle. Flow cell assembly 94 includes a base 98, for example madefrom aluminum, a first bore 100, and a second bore 102. Optical platesforming the sample cell are sized to be accommodated in first bore 100(similar to that shown in FIG. 8B for flow cell 94′ to be describedhereinafter). The tilt angle (described below) causes reflections of theincident IR radiation to be directed out of the optical path.

FIG. 8B, however, shows a preferred flow cell assembly embodiment 94′having a built-in compensator window. Flow cell assembly 94′, inaddition to base 98, first bore 100, second bore 102, includes a samplecell 104, a third bore 106, a fourth bore 108, and a compensator windowor plate 110. Sample cell 104 includes a first optical plate 112, asecond optical plate 114, and a spacer 116.

Plates 110, 112, and 114, preferably comprise zinc selenide (ZnSe)material, but may alternatively be formed using any other relativelyhigh index of refraction materials, such as Ge, Si, AMTIR, CdTe, and thelike. Spacer 116 is, in a preferred embodiment, approximately 0.1 mmthick. Each one of sample cell 104 and compensator window 110 haveassociated therewith a respective normal axis, designated N_(s), andN_(c), respectively. IR radiation typically propagates along a principalaxis designated P in FIG. 8B. In accordance with the invention, samplecell 104 and compensator cell 110 are each tilted a tilt angle θ, whichmay be between about 15 degrees and 50 degrees, preferably between 20degrees and 40 degrees, more preferably between about 20 degrees and 25degrees, and most preferably about 20 degrees in a constructedembodiment. Selecting the tilt angle to reduce undesirably fringingartifacts depends on a variety of factors including, but not limited to,the optical materials used (e.g., for the optical elements), whether theoptical element is coated, and the spectral features of interest.Preferably, the effective thickness of compensator window 110 issubstantially the same as the effective thickness of sample cell 104 aswell as the respective indices of refraction (relative to the filledsample cell).

FIG. 8C shows a view of flow cell assembly 94′ as viewed from the toprelative to the orientation depicted in FIG. 8B.

FIG. 8D shows a perspective view of first plate 112. First plate 112includes a pair of bores 118 extending through the thickness thereof(which in a constructed embodiment is approximately 2 mm thick, 32 mm(approximately 1.25″) in diameter), and a circumferential groove 120.Compensator window 110, in the described embodiment, comprises zincselenide material, is approximately 25 mm in diameter, and approximately4 mm thick.

FIG. 8E is a cross sectional view taken substantially along linesdesignated 8E—8E illustrated in FIG. 8D. Plate 112 includes a firstsurface 122, and a second surface 124. Given the orientation shown inFIG. 8B, second surface 124 faces second plate 114, while first surface122 defines the first surface upon which IR radiation impinges from IRsource 84. Fluid sample 12 may be introduced through a small tubedisposed or in communication with one of bores 118 to thereby fill thevoid between plates 112, 114 established by spacer 116, and thence flowout of the other one of bores 118 into an outlet tube coupled to wastereceptacle 48. Groove 120 provides a path for particles larger than thespacer thickness (e.g., as constructed, 0.1 mm) to flow from input tooutput without blocking the flow of the fluid sample.

Lateral translation means 96, as shown in FIG. 9, is coupled to and iscontrolled by controller 28 to move flow cell assembly 94′ between afirst position wherein compensator window 110 is optically intermediateIR source/lens 84/86 and detector assembly 88, and a second position (asshown in FIG. 9) wherein sample cell 104 is optically intermediate IRsource 84/lens 86, and detector assembly 88. The first position is usedby apparatus 10 when a background or reference reading is desired.Regular collection of the background insures optimum photometricperformance and increased baseline stability of the system.

It should be understood that the described FTIR system is atypicalinasmuch as it uses a convergent IR radiation beam, and not a collimatedor parallel propagating type beam. It should further be understood thatuse of such a convergent radiation beam directly leads to an advantageof a more compact system, as described above. However, due to theconvergent nature of the IR beam, along with the tilting of sample cell104, and the further relatively high index of refraction of sample cell104, an actual displacement (as well as defocusing) of the image throughthe sample cell occurs (this is an exaggerated shift to the left in FIG.9). It should be understood that the detector 92 is selected, and islocated spatially, optimally, for the arrangement as illustrated in FIG.9 (i.e., sample cell in place—the second position). A background orreference reading taken through air, or even through an untilted cellwould allow the beam to pass through without changing direction. Withoutsuch a change in direction (i.e., spatial translation, ultimately), theIR radiation beam, when taking the background reading, would miss, orperhaps only imperfectly impinge on detector 92 (as positioned forreadings through the sample cell).

Therefore, in accordance with yet another aspect of the presentinvention, the compensator window 110 is made of the same material,having approximately the same thickness and index of refraction, andfurther, is disposed at approximately the same tilt angle, as the samplecell 104. Producing substantially identical conditions for beamrefraction in the compensator window as for the sample cell means: thatthe focused images of both the sample beam and the reference(background) beam will coincide in space at the selected detectorlocation. Without this aspect of the invention, a larger detector wouldhave to be used to effectively capture both beams (an alternateembodiment required a 2 mm target area instead of a 1.3 mm target areadetector for the embodiment using flow cell assembly 94′). Such anenlarged detector has shown a reduced sensitivity (signal-to-noise) byup to a factor of 2. In sum, by matching the overall properties ofthickness and index of refraction for both the sample cell, and thecompensator window, the detector 92 can remain fixed in space as lateraltranslation means 96 moves the flow cell assembly between the first andsecond positions.

Of course, alternate configurations are possible for compensator window110, in terms of the composition of materials used, thicknesses, indexof refraction, etc. that are within the reach of one of ordinary skillin the art, and are included within the spirit and scope of the presentinvention.

FIG. 10 shows, in greater detail, OES assembly 26. In addition to sparksource power supply 56, enclosure 58, and spectrometer assembly 60, OESassembly 26 further includes a high voltage supply 126, an upperelectrode 128, a lower electrode 130, a collimator 132, a bifurcatedfiber optic cable 134, and wherein spectrometer assembly 60 includes afirst spectrometer 60 ₁, and a second spectrometer 60 ₂. Assembly 26also includes an analog-to-digital conversion and interface card 136,which may be mechanically disposed in the passive back plane andintelligently linked with the software of apparatus 10 by way ofappropriate software drivers.

Spark source power supply 56 and HV supply 126 may comprise conventionalapparatus. Applicants commercially obtained the same from ArunTechnology Ltd., Unit 16, Southwater Industrial Estate, Station Road,Douthwater, West Sussex, England, under part number: ATL410911.Electrodes 128 and 130 are preferably made primarily of silver material.However, other materials may be used, such as, for example, tungsten.

FIG. 10 further shows transfer assembly 20, which causes fluid sample 12to flow through a through-bore 137 portion of lower electrode 130, andthence to waste receptacle 48. Computer controller 28 controlsapplication of high voltage across electrodes 128/130 to therebygenerate a spark. The frequency of sparking is programmable and may bevaried by the operator by appropriate selection of a spark frequencyparameter value. Spark frequencies may include 120, 150, 200, 250, 300,350, 400, and 450 Hz.

FIG. 10 further shows collimator 132, which may comprise conventionalapparatus, such as is available from General Fiber Optics, a subsidiaryof Sigma-Netics, of One Washington Avenue, Fairfield, N.J. 07006. Thebifurcated cable 134 and collimator 132 are, in a constructedembodiment, provided together as a unit. Together, they function toacquire light emitted in the region of electrodes 128/130, and carrythat light to both spectrometer 60 ₁, and spectrometer 60 ₂.

First spectrometer 60 ₁ is configured to receive the light or radiationgenerated by electrodes 128/130 and generate a first spectral pattern inresponse thereto. Second spectrometer 60 ₂ is configured to receivesubstantially the same light or radiation as the first spectrometer andgenerate a second spectral pattern. In a preferred embodiment, thesecond spectral pattern is different from the first spectral pattern inboth spectral range covered as well as resolution.

Spectrometers 60 ₁ and 60 ₂ may comprise conventional and known,commercially available optical emission spectrometers. In a constructedembodiment, the spectrometers 60 ₁ and 60 ₂ are a model SD 2000commercially available from Ocean Optics, Inc., Dunedin, Fla., USA. In apreferred embodiment, spectrometer 60 ₁ is configured with a resolutionof approximately 0.3 nm across a spectral range from about 200 nm toabout 340 nm. This constitutes primarily the UV range. Spectrometer 60 ₂has a resolution of approximately 1.0 nm and is configured to produce aspectral pattern over a spectral range nominally between about 180 nm to880 nm (constitutes UV-visible range). In the constructed embodiment,each spectrum is imaged using a 2048 pixel charge couple device (CCD)array spectrograph. Of course, functionally equivalent sensing devicesmay be substituted and remain within the spirit and scope of theinvention.

A/D converter 136 may comprise conventional and known apparatus. A/Dconverter 136 is provided for receiving a substantially analog signalcorresponding to the charge accumulated on the pixels of the CCD sensorduring an exposure time, and converting each into a respective digitalword. For example, each digital word may be a twelve-bit digital word.Software drivers are available, for example from Ocean Optics for theirproducts, that enable one of ordinary skill in the art to use thespectrometer output from higher level software programs. In oneembodiment, the output of first and second spectrometer 60 ₁ and 60 ₂each comprise a text file. The text file may include two columns. Thefirst column may include an increasing series of wavelength valuescorresponding to the 2048 pixels in the CCD. The second column mayinclude a series a values representing an intensity or magnitude at thecorresponding wavelength. The software drivers orchestrate thecoordination of the sampling of the analog signal presented to A/D 136from spectrometers 60 ₁ and 60 ₂. In the constructed embodiment, thespectrometers arrive from the manufacturer pre-calibrated. That is, eachspectrometer 60 ₁ has associated therewith a predetermined calibrationequation (e.g., in quadratic form) that provides the wavelength value ofcolumn 1 as a function of pixel number. This is why the wavelength valueof column 1 corresponds to the pixel numbers (i.e., via the calibrationequation).

Typical spectrometers used as atomic emission spectrometers generallyfeature larger, higher resolution instruments, such as those having aresolution of 0.05 nm or better (“high resolution”). The spectrometersemployed in apparatus 10 are considered “low resolution” spectrometers,in view of the foregoing stated resolutions.

First spectrometer 60 ₁ is used for most of the wear metals and dirt andcontaminate elements (i.e., for detection, and for concentrationdetermination). Second spectrometer 60 ₂ is used, in a constructedembodiment, for two basic purposes. The first purpose involvesdetermining elements in the visible spectrum, notably sodium andpotassium, which do not require higher resolutions for adequatedetection and may not be covered in the wavelength range of firstspectrometer 60 ₁. Second, for the determination of wear metals at highconcentrations. In the later case, the second spectrometer 60 ₂ enablesapparatus 10 to provide an extended dynamic range, thereby detectingboth high and low concentrations of wear metals and contaminateelements, essentially simultaneously, without the need to reset thespectrometer gain, thereby eliminating the need for effectivelyredundant measurements.

It should be understood that the resolution of both spectrometers 60 ₁and 60 ₂ are much lower than conventionally considered sufficient fordetermination of elemental emission lines. However, the use of fullspectral presentation (i.e., substantially continuously valued over awavelength range, as opposed to using higher resolution instruments withsingle photo multiplier tubes coupled with a large monochromator thatdetect particular emission lines) enables apparatus 10 to implementnumerical data processing techniques, such as peak area integration,curve resolution and curve fitting, and full or partial spectralfitting, and regression analysis. The latter feature corresponds toeither classical least squares fitting methods, or multivariatestatistical methods, such as PCA (principal components analysis), PCR(principal components regression), PLS (partial least square), LWR(locally weighted regression) methods, or neural networks. The methodsnoted, as well as other approaches to univariate or multivariateanalysis, applied as described below on the acquired sample spectraldata, enable the analysis of analyte components (i.e., fluid sampleconstituents) that would otherwise remain unresolved.

In operation, fluid sample 12 is excited by the spark. When theelectrons of the atoms of the constituent materials (as well as thefluid sample) contained therein, are driven to higher energy states bythe electrical discharge, they are in an unstable state. When theelectrons eventually relax to a ground state, photons are emitted. Theenergy—or wavelength—of these photons is indicative of the particularatom responsible for the emission. Thus, the detection of light at thatwavelength is an indication of the presence of that particular atom inthe sample. Moreover, the more light emitted under conditions ofconstant electrical excitation, the more of these particular atoms arepresent in the sample. The relationship between concentration andintensity is substantially linear (monotonically increasing) over a verywide dynamic range; provided, however, that the excitation strength isrelatively constant. This is difficult to achieve using spark as theexcitation source.

Thus, in accordance with yet another aspect of the present invention,methods and apparatus are provided to condition raw spectral data toproduce stable, informationally significant sample spectral data.

Raw spectral data from the spectrometers generally takes the form of anarray of pixel values representative of wavelengths and associatedspectral intensities over a predetermined spectral range. As notedabove, each ordered pixel number may have a wavelength associatedtherewith based on a preexisting calibration equation. Variability inboth the wavelength (i.e., wavelength shift) and intensity presentchallenges overcome by this aspect of the present invention.

Wavelength shift may occur due to (i) the inability to makespectrometers that are physically identical; and (ii) externalconditions such as temperature, humidity, atmospheric pressure,vibration, and electrical pick-up (which may result in wavelengthcalibration changing as a function of time). Variation in the intensityof certain emission lines over multiple sample spectra (even for thesame sample—same concentration level—taken closely in time) may occur inthe OES portion of apparatus 10, primarily due to the use of spark orarc emission technology, in which a constant strength of excitation isdifficult to achieve.

It thus bears emphasizing that disturbances that allow a drift in thesample spectral data in the wavelength axis render subsequentmathematical analysis more complicated or impossible. This is becauseparticular spectral emission lines (or spectral features) of interestmay be confused or mistaken for other irrelevant features. Moreover,spectral emission lines which overlap (due to the “low resolution” ofthe spectrometers used) are much more difficult to decompose in thepresence of drifting spectral emission lines. Therefore, for the rawsample spectral data to be compatible with both (i) the data taken onother apparatuses 10, and (ii) the data taken on the particularapparatus 10 as a function of time, the relationship between pixelnumber and wavelength (i.e., “wavelength calibration”) must remainsubstantially constant (i.e., no appreciable pixel to wavelength shift).

In accordance with the invention, the OES portion of apparatus 10 usesradiation from spark emission to produce a spectral pattern havingspectral features, such as emission lines, to quantify constituents in afluid sample. The emitted radiation, in addition to relating to atoms ofthe fluid sample constituents (e.g., wear metals, additives, and thelike), define spectra including a plurality of spectral features such asemission lines, indicative, at least in part, of (i) the composition ofthe electrodes, which in the preferred embodiment comprise silvermaterial, and (ii) hydrocarbons in the lubricant itself. Of course, tothe extent that electrodes 128/130 are comprised primarily of analternate material, such as tungsten, the background spectrum would bedifferent, and include a plurality of spectral features indicative oftungsten. An additional plurality of spectral features would be presentfor an alternate electrode material and/or combination/alloys thereof.

The plurality of spectral features, such as emission lines, for silverhave a pre-existing, predetermined known wavelength values. These knownspectral features, due to the composition of the electrodes themselves,may be considered absolute wavelength standards for the operation ofapparatus 10. The acquired sample spectrum of a fluid sample generatedby the spectrometer of apparatus 10 may be regularized (with respect towavelength drift) by reference to one or more of these spectral featuresdrawn from the background.

X-Axis (Wavelength) Correction

X-axis correction is achieved generally by first establishing a mappingbetween wavelength and pixel position using spectra exhibiting knownabsolute wavelengths. This allows spectral determinations to beconducted in wavelength space as opposed to pixel space. In wavelengthspace, the positions of multitudes of emission lines of differentelements are well known, whereas, the ability to locate needed spectralinformation is much more difficult when the x-axis is labeled only bypixel number.

To effect this mapping, one can exploit the existence of the“background” emission lines always present in spark emission spectragenerated on the emission spectrometer on apparatus 10. This iscompleted by respectively correlating respective a pixel position of aset of background emission lines in a spectrum and known wavelengthsusing regression techniques. This mapping establishes a standardwavelength for each pixel. For example, if one had 2048 pixel values, aset of 2048 wavelengths would be generated and the wavelength positionof the set of background emission lines are known with respect to thisstandard set of wavelengths.

In a constructed embodiment, wavelength drift, if any, is corrected byperforming the following steps, designated by reference numerals 145-148in FIG. 18. In addition, the examples to follow are generally withreference to spectrometer 60 ₁, (0.3 nm resolution). It should beunderstood, however, that the same principles apply to spectralprocessing with respect to spectrometer 60 ₂ as well (e.g., 1.0 nmresolution).

The first step, step 145, involves defining a background spectrum havinga plurality of spectral features (e.g., emission lines) indicative atleast in part of the composition of the electrodes. The term “backgroundspectrum” is defined in the foregoing paragraphs. This step may beperformed by the substep of taking an inventory of the multitude ofspectral features that make up the background spectrum for a particularconfiguration (e.g., silver electrodes). Some of these spectral featuresmay be better than others for X-axis correction so a selection step maybe performed (see below) . This defining step is generally performedbefore the apparatus 10 is deployed to analyze samples.

The second step, step 146, involves selecting at least one, andpreferably a plurality of, background spectral features (e.g., multipleemission lines) from the plurality of spectral features that make up thebackground spectrum (e.g., in the illustrated embodiment, the spectrumindicative of the silver composition of spark electrodes 128/130). Eachone of the selected emission lines has a known wavelength. In aconstructed embodiment, the selected emission lines comprise the 224.64nm, 241.32 nm, 243.78 nm, 247.86 nm and 335.98 nm emission lines. Ofcourse, in any particular embodiment, other emission lines and/orspectral features of the background spectrum may be used. This step isgenerally performed before an apparatus 10 is deployed for sampleanalysis. It is preferable to use a set of lines which span the entirespectral range.

The third step, step 147, involves, after acquiring a sample spectrum,determining respective wavelength values for the set of backgroundemission lines. The raw spectral data of the fluid sample, may comprisean n-row (where n=number of pixels, e.g., 2048), two-column array ofdata. Each row contains a wavelength value and a corresponding intensityvalue. For spectrometer 60 ₁, the wavelength values may spanapproximately 200-340 nm, while for spectrometer 60 ₂, the wavelengthvalues may span approximately 180-880 nm. As described hereinbefore, thewavelength values in the array may be derived from using a pixel numberin connection with a calibration equation that is “built-in” to thespectrometer (or associated therewith ahead of time through software).

Depending on wavelength accuracy needed, wavelength determination may bedetermined in a number of ways. In one embodiment, the standardwavelength point corresponding to the maximum of the emission line maybe used. That is, identifying an emission line may involve locating a“peak” or “maximum” intensity within a relatively small wavelengthrange. This may be done using any known mathematical analysis. In aconstructed embodiment, for example, apparatus 10, through programmedsoftware, examines a predetermined number of intensity values for alocal maximum in a range where the sought-after background emission lineis likely to be found. Once the local “peak” is identified, thecorresponding wavelength value, as indicated in that row of the dataarray, defines the actual location (wavelength) of the sought-afteremission line. The foregoing wavelength value determination procedureprovides x-axis calibration accuracy to within about 1 pixel, since theprocedure simply identifies the row (i.e., pixel) having the “peak”intensity within a range. For higher accuracy, algorithms can be used tobetter determine the wavelength value corresponding to the emission line(peak) maximum. This can be done using known mathematical analysis forpeak fitting. For example, the peak line profile may be “fit” to a welldefined functional form, such as a Gaussian lineshape, or a moreempirical version of peak fitting (such as described above) or such asthat of LaGrange interpolation or a cubic spline might be employed. Forexample, since there are 2048 pixels (i.e., data points) spread out overabout 140 nm of spectral range in the illustrated embodiment ofspectrometer 60 ₁, a nominal pixel spacing is about 0.07 nm/pixel.Moreover, since the resolution of spectrometer 60 ₁, is about 0.3 nm,the raw spectral data includes, theoretically, a little over 4 datapoints (pixels) per resolution. Since an emission line will berepresented as being no thinner than about 0.3 nm, there will be atleast 4 data points thereover. Moreover, in practice, a particularemission line may span as many as 6-10 data points (pixels). These datapoints can be “fit”, for example, using a cubic spline or any otherknown fitting technique. The result of the “fit” is an equation that canbe used to determine the actual wavelength value of the “peak”, “mean”or other identification criteria of the sought-after emission line inthe sample spectrum. This approach provides the capability to determinewavelength values “in-between” rows (i.e., pixels) of the data array,and thus provides an accuracy of greater than 1 pixel. This step isperformed for each spectral feature (e.g., silver emission line)selected as an internal absolute standard for apparatus 10.

The fourth step, step 148, involves, generally, translating the samplespectrum with respect to wavelength based on a correction to theinternal, absolute wavelength standard. The translating step may includefour (4) basic substeps: determining offsets for each emission line,determining a total wavelength offset for the sample spectrum,converting from wavelength space to pixel space (i.e., generating apixel shift number), and shifting the intensity values in the acquiredsample spectrum.

The first substep involves determining a wavelength offset for eachbackground spectral feature (e.g., emission line), each taken between(i) the expected wavelength value of a background emission line (basedon known absolute standards), and (ii) the actual, measured wavelengthvalue (i.e., actual location) of the background emission line asindicated in the sample spectrum. In the foregoing example, if thelocation of the “224.64 nm” silver emission line, as indicated by thesample data is 225.64 nm, then there is a 1 nm shift to the right. In aconstructed embodiment, determining offsets is done for each emissionline being used as an absolute wavelength standard.

The second substep involves determining a composite wavelength offsetfor the acquired sample spectrum. This is completed by using wavelengthoffsets for all the emission lines used as absolute wavelengthstandards. In a constructed embodiment, a simple arithmetic average ofthe individual wavelength offsets is employed to determine the compositewavelength. For example, to determine an average wavelength offset, eachoffset (in wavelength terms, e.g., 1 nm) is assigned an orientation(e.g. to the right (+) or left (−)). Then, an arithmetic average istaken.

The third substep involves converting the average offset calculatedabove in wavelength space to pixel space. To convert the averagewavelength offset to a pixel shift, the arithmetic average is convertedto pixels using the nominal pixel spacing of 2048pixels/(340−200)nm=14.6 pixels/nm (assuming spectrometer 60 ₁). Forexample, an average wavelength offset of +2 nm converts to about 29pixels. This value is a pixel shift number, and the orientation is tothe right.

The fourth substep, which actually achieves the x-axis correction,involves shifting each intensity value in the column of intensity valuesin the data array (i.e., sample spectrum) by the calculated pixel shiftnumber, either up or down. The wavelength correction process may beaccomplished immediately after the sample data acquisition of the fluidsample without further data acquisition, inasmuch as the backgroundspectral features (e.g., the silver emission lines that act aswavelength standards) are acquired simultaneously with the sample data.Moreover, in this case, the background emission lines are “naturally”occurring as a result of the experimental configuration (i.e., due, inpart, to the material or composition of the electrodes) and therefore noexternal standard needs to be added.

In an alternate x-axis correction embodiment, accuracy greater than 1pixel may be obtained. First, the manufacturer's calibration ofspectrometers 60 ₁, and 60 ₂ may be replaced by running variousconstituents, preferably the wear metals of interest, through apparatus10. These constituents will exhibit emission lines having knownwavelength values, as published in the known literature. The resultingspectral data obtained thereby may be analyzed and a relationshipbetween wavelength and pixel number may be obtained. For example, for athird-order fit:

λ=αP+βP ² +γP ³+Δ

Once this process has been performed, spectral features (which includeemission lines) may be selected from the background spectrum for use aswavelength standards during sample acquisition and analysis. Forexample, where silver is used for the electrodes 128/130, emission linescapable of being resolved by spectrometers 60 ₁, and 60 ₂ may be used(as in the constructed embodiment). However, the alternative embodimentis not as limited, and may include any spectral feature (e.g., severalemission lines, indicative of the electrode material, that are too closetogether to be uniquely resolved so they therefore appear as a“bump”—this “bump” may be selected as a spectral feature). This spectralfeature may not have a predetermined, known absolute wavelengthassociated therewith available in the literature. However, an absolutewavelength value can nonetheless be assigned to the spectral feature, sothat it can be used just like an emission line as follows. Thebackground spectral feature has a number of data points (pixel no.:intensity) associated therewith. These data points may be analyzed tofind a “peak”, “mean”, or other meaningful representation of thespectral feature. For example, the “peak” may be expressed as pixelnumber (e.g., both integral and fractional parts thereof). The pixelnumber of the “peak” may then be substituted into the above equation toyield a wavelength value (“secondary wavelength standard”). Thisstandard may then be carried forward for use during acquisition andanalysis of a sample.

Next, analysis of the fluid sample results in raw spectral data beingprovided to apparatus 10 (e.g., in the form of wavelength value:intensity value for the 2048 pixels). The plurality of “spectralfeatures” are then identified in the sample spectrum, and, using thesame “peak” detection algorithm, a corresponding plurality of spectralfeature locations are generated (e.g., pixel number xxx.xx as thelocation of the spectral feature as indicated by the array of values).Since the “absolute wavelength” of these selected spectral features hasnot changed (i.e., they are absolute), a new calibration equation may bederived by any known fitting procedure. That is, apparatus 10 now hasavailable a plurality of ordered pairs of data in form of (APL₁: λ₁;APL₂:λ₂, . . . , APL_(n):λ_(n)), where APL_(i) is the actual pixellocation of spectral feature i from the sample spectrum array, and,λ_(i) is the absolute wavelength associated with spectral feature i.Thus, an equation providing λ as a function of P (pixel number) may beproduced (“new calibration equation”).

Next, using the new calibration equation, the array of raw spectraldata, which is in the form of wavelength (old calibration):intensity,may be translated or mapped with respect to wavelength to an x-axiscorrected array. This translation is done by applying the new equationto each data point in the raw data spectrum. That is, the intensity foreach point will remain the same, but the wavelength value will berecomputed by substituting pixel numbers into the new equation to obtainnew wavelength values. For example, for pixel number=1, evaluate the newequation for the first data point and associate the new wavelength valuewith I₁ (intensity for data point number 1). Next, substituting pixelnumber=2 and associating the resulting wavelength value with I2, and soon.

At this point, apparatus 10 has available to its software a spectrum ofthe fluid sample, corrected with respect to wavelength to compensate,for example, for drift. However, the spacing between points may not beuniform, since the new calibration equation will in many instances benon-linear.

Therefore, a further step may be performed so that all the data points(e.g., 2048 points expressed in wavelength value: intensity form) areevenly spaced as a function of wavelength. For example, the spacing maybe selected to uniformly cover the spectral range. Thus, forspectrometer 60 ₁, with a spectral range of 140 nm (340−200 nm) and 2048pixels, the spacing should be about 0.07 nm. Thus, after standardizing,which may be accomplished by conventional interpolation techniques, thedata points will be uniformly spaced (e.g., 200.00 nm: I₁; 200.07 nm:I₂; 200.14 nm: I₃, etc.). Standardizing (i.e., imposing the x-axiscorrected sample spectral data on a uniformly spaced grid) simplifieslater arithmetic operations, to be described in detail hereinafter. Thisset of standardized wavelengths can then be considered the standard setof wavelengths for all spectrometers.

Y-Axis (Intensity) Normalization

With respect to intensity variation, it bears repeating thatestablishing a uniform excitation strength spark emission is acircumstance difficult to achieve in practice. This variation introduceschallenges solved by the present invention, inasmuch as the linearrelationship between emission line intensity and constituentconcentration (i.e., “concentration” is the parameter that the expertsystem needs as an input) is dependent on a constant strength ofexcitation.

By way of example, FIG. 11 shows three background reference spectra 140,142 and 144 taken from three different samples of clean, base oils(i.e., simple mineral oils without additives). Based on FIG. 11, onemight reasonably believe that the entire electrode emission strengthvaries by a factor of 5 or more.

While FIG. 11 illustrates the three reference spectra at the blue end ofthe spectrum (220-250 nm), FIG. 12 shows the same three sample spectra140, 142 and 144 with emphasis on the red end (335-338 nm wavelengthrange). Note that the variation in intensity is relatively reduced.

In accordance with still yet another aspect of the present invention,the variation in the emission strengths or intensities of constituents(or analytes) to be measured, which is caused by variability of thespark (i.e., electrical discharge), may be reduced by using theintensity of a background spectral feature, such as an emission line(i.e., one associated or indicative at least in part with the materialof the electrodes) for normalization. In a constructed embodiment, theintensity of the 336 nm silver “emission line” is used as a normalizingquantity. The emission line “intensity” comprises, in the constructedembodiment, the area under the curve for the 336 silver emission line(as shown in FIG. 12) in the acquired sample spectrum.

Not all emission lines associated with the composition of the electrodesare desirable or useful in reducing intensity variation. However, inaccordance with the present invention, a method is provided fornormalizing an intensity of a constituent emission line of a measuredelement from the acquired sample spectrum of a fluid sample generated bya spectrometer having a pair of electrodes. FIG. 19 shows a flowchartdiagram of the method in steps 149-151. The method includes two basicsteps. The first step, step 149, involves selecting at least onespectral feature, such as an emission line, from a background spectrumhaving a plurality of spectral features (e.g., emission lines)indicative at least in part of the composition of the electrodes and/orbase oil or similar solvent carrier wherein the selected spectralfeature (e.g., emission line) has an intensity variation characteristic.The second step includes normalizing the intensity of a constituentemission line of a measured element with respect to sample spectrum withrespect to the “intensity” of the selected spectral feature (e.g.,emission line). This second step involves a measuring step, as shown instep 150, and a transforming step, as shown in step 151. In step 150(FIG. 19), an intensity of the background spectral feature (e.g.,emission line) is measured. In step 151, the sample spectrum istransformed with respect to intensity in accordance with the measuredintensity of the selected background spectral feature.

It bears repeating that the intensity of some, but not all, backgroundspectral features (such as emission lines) of a background spectrumcorrelate to the emission line intensity of constituents in a fluidsample to be measured and can be used for normalization. Normalizationby, for example, ratioing the emission line intensity of an element tothat of a background line results in (i) a reduced variability and hencean improved elemental concentration determination and (ii) a measurementthat can be determined adequately in a shorter period of time (i.e.,less signal averaging necessary).

Accordingly, in yet another aspect of the present invention, a methodfor selecting the background spectral feature (such as an emission line)having a desirable intensity variation reduction characteristic isprovided. This method may be performed prior to the run time analysis ofa fluid sample, so that all the run-time software has to do is to lookup the established background spectral feature (e.g., emission line).The approach is to evaluate several candidate background spectralfeatures (e.g., emission lines) for their respective capabilities toreduce variation of the intensity of a constituent of interest.

The first step involves identifying an emission line associated with atleast one constituent in a fluid sample. For example, the selectedemission line may be the 324 nm emission line associated with copper, ameasured wear metal.

The second step involves selecting a first set of spectral features(e.g., emission lines) from the plurality of spectral features (e.g.,emission lines) associated with the background spectrum. The first setincludes the likely candidates of background spectral features thatmight be used as a normalizing standard. The first set may includesimply just one emission line.

The third step involves obtaining a predetermined number of spectra ofthe fluid sample, preferably a single fluid sample. The fluid samplepreferably contains the above-mentioned constituent (e.g., copper) of aknown concentration. The predetermined number of spectra shouldpreferably be statistically significant, and may be at least 20 spectra,preferably at least 30 spectra, most preferably at least 50 spectra.However, using a higher number of spectra will generate results that aremore statistically significant.

The fourth step involves determining a first intensity variation of theemission line associated with only the constituent (i.e., the 324 nmcopper emission line) over the predetermined number of spectra. Forexample, over a predetermined number of spectra for a fluid sample,which contained a constant concentration of the constituent copper, theobserved intensity variation, where the electrodes were controlled to aspark rate of 120 discharges of per second, was approximately twentypercent (20%) (notwithstanding a constant concentration of copper, andfurther, replicate measurements done closely in time).

The fifth step involves assessing how effective each candidate is atreducing variation. This step involves determining, for each spectralfeature (e.g., emission line) in the first set, a respective secondintensity variation over the same set of replicate spectra. In apreferred embodiment, this step comprises two substeps: (i) for each ofthe predetermined number of spectrum mentioned above, dividing the“intensity” of the emission line of the constituent by the intensity ofthe respective background spectral feature (e.g., emission line) in thefirst set to thereby produce a predetermined number of ratio values; and(ii) calculating a second intensity variation using the predeterminednumber of ratio values.

For example, for each of the predetermined number of spectra, the“intensity” of the copper emission line is divided by the “intensity” ofthe background emission lines in the first set (e.g., the 336 nm silveremission line as well as any other candidates in the first set) todevelop a series of ratio values. The variation of this series is thendetermined and associated with the respective background spectralfeature (e.g., 336 silver emission line). For example, when theintensity of the 324 nm copper emission line is divided by the intensityof, for example, the 336 nm silver emission line, the resultingvariation, over the predetermined number of sample spectra, was, in oneconfiguration, approximately eight (8%) percent.

The sixth step involves selecting emission lines from the first set thathave a second intensity variation that is less than the first intensityvariation to thereby form a second set of emission lines for possibleuse for normalization. For example, since the variation in intensity ofthe normalized 324 nm copper emission line using the 336 nm silveremission line (8%), is less than the variation in the intensity of the324 nm copper emission line without any normalization (e.g., as notedabove, approximately 20%), the 336 nm silver emission line represents asatisfactory standard to use in reducing intensity variation of sparkemission spectra. The 336 silver line thereby goes into the second setof emission lines.

The seventh and final step for selecting a background spectral feature(e.g., emission line) suitable for intensity normalization involvesselecting one of the spectral features from the second set based onpredetermined criteria. One criteria comprises the degree to whichvariation is reduced.

EXAMPLE Determining Concentration of a Wear Metal

This example pertains to the determination of the concentration ofcopper in a used engine oil sample. The first or preliminary step mayinvolve identifying a background spectrum having a plurality of spectralfeatures indicative at least in part of a composition of the electrodes.For example, FIG. 13A shows the spectrum of a reference base oil ormineral oil. Most of the emissions are a property of the electrodes.FIG. 13B shows the effect of additives which are often present in newoils. Emission lines 152, for example, correspond to the additivemagnesium. Emission lines 152 may also be useful as emission lineshaving a known, absolute wavelength for purposes of correcting forwavelength drift as described above under the heading “X-AXISCORRECTION”. FIG. 14 illustrates a further example of a new oil havingmagnesium additive emission lines 154, copper additive emission lines156, and calcium additive emission lines 158. FIGS. 15A-15C show furtherexemplar spectra of three different “new” oils. The foregoing spectra,as well as spectra from other new oils can be stored in the memory ofapparatus 10 for subsequent use. This step does not need to be performedduring run time, and preferably is done in advance thereof. In oneembodiment, the background spectra are standardized (i.e., uniformwavelength spacing).

Next, an intensity calibration curve is built. This curve will be usedfor correlating intensity to a concentration. This may be doneempirically. For example, a known concentration of a constituent isintroduced into apparatus 10 and analyzed. Next, a selected referencespectrum (e.g., FIGS. 13, 14 and 15) is subtracted from the raw spectraldata resulting from the analysis. This spectral substraction isexplained in detail below. Next, the resulting “peak” intensity of aspectral feature (such as an emission line associated with theconstituent for which the curve is being built) is then correlated tothe known concentration. In a constructed, preferred embodiment, thearea under the curve representing the emission line peak is measured andis associated with the corresponding known concentration. This is donefor all the constituents to be analyzed by apparatus 10. This step ispreferably done ahead of the time when a sample is analyzed. Theplurality of intensity calibration curves may be stored in non-volatilememory, such as on magnetic media for subsequent use.

Next, a spectral feature of the background spectrum is selected for useas a normalizing ratio. This may be done as set forth above under“Y-AXIS Correction”. In a preferred embodiment, the area under the curveof the 336 nm silver emission line is used, based on its ability toreduce intensity variation.

Next, the fluid sample under test is introduced into apparatus 10 andanalyzed thereby, including analysis by OES assembly 26. The resultingraw spectral data is then corrected for x-axis drift, if any, asdescribed above, and is illustrated in steps 145-148 of FIG. 18.

The next steps involve determining a characteristic emission lineassociated with the selected constituent element of interest in theexample, namely copper. In this example, the characteristic emissionline may be the 324 nm emission line. What emission line to choose maydepend on what lines are strongly indicative of copper, whether thereexists or expected to exist interfering elements (i.e., elements thathave emission lines that are located close or nearby to the selectedconstituent emission line) in the sample under test. The spectralfeature selected to represent the targeted constituent may correspond tothe spectral feature used to generate the above-mentioned intensitycalibration curves.

Next, a spectral subtraction step is performed which involvessubtracting a reference spectrum (i.e., of the type illustrated in FIGS.13A-13B, FIG. 14 and FIG. 15A-15C) from the sample spectrum. Thisspectral subtraction step minimizes and/or eliminates undesirable and/orunrequited background emission lines, and so long as there is spectralregistry (accomplished by X-axis correction), a simple subtraction maybe done to perform this step. Since the stored reference spectra areunscaled, an adjustment to the intensity of the reference spectrum to besubtracted must be made. This adjustment may be made by locating aspectral space where there are no significant spectral features, suchas, for example, around 300 nanometers. Then, adjusting the amplitude ofthe reference spectrum until the subtraction in the located spectralspace nulls (i.e., produces a true zero difference). In practice, aseries of scaled reference spectra (e.g., 1.1*reference, 1.0*reference,0.9*reference, 0.8*reference, etc.) are each subtracted and theresulting region is analyzed. The best (i.e., lowest averageamplitude—noise) is used.

In addition, regarding spectral registry, it should be understood thatthe subtraction process can be performed, numerically, in a variety ofways. For example, in a constructed embodiment, both the referencespectra and the sample spectrum comprise 2048 data points. Thesubtraction may thus be performed on a point-per-point basis (i.e.,point 1 (sample)—point 1 (reference)). The sample spectrum may havedifferent wavelength values, on a per point basis, than the referencespectra. However, the wavelength divergence may not be substantialenough to cause serious difficulties in locating spectral features. Inan alternate embodiment, however, both the reference spectra and thesample spectrum are standardized prior to subtraction (i.e., each havethe same starting wavelength value, and each have the same, uniform,wavelength value spacing between data pairs).

The next step involves measuring the area under the silver 336 nmspectral feature.

The next step involves measuring the area under the 324 nm copperemission line.

The next step involves dividing the 324 copper emission line “intensity”(e.g., area) by the 336 silver emission line “intensity” (e.g., area) toarrive at a normalized ratio value.

Finally, the intensity calibration curve for copper is used to determinethe concentration of the constituent element copper in the fluid sampleas a function of the copper area/silver area ratio value. Theconcentration of copper, as well as other constituent elements, are thenprovided to an expert system for diagnosis.

EXPERT SYSTEM

Apparatus 10 acquires analytical data from various measurementsubsystems, under the control of controller 28. After processing asdescribed above, the constituent concentration data, for exampleconcentrations as expressed in parts per million (PPM) of various wearmetals, percentage water, and the like, are then provided to an expertsoftware system. The expert system, in connection with a set of rules(“Rules”), and a database, generates diagnostic statements regarding theassessment of the condition of the fluid (e.g., oil) and/or theoperating equipment associated therewith.

The expert system executes on controller 28 and is operative to evaluatethe plurality of Rules in response to the constituent concentrationparameters as well as other data and produces a plurality of outputsignals. The expert system then determines a condition or state of thelubricating oil or functional fluid and/or the equipment (or componentthereof), from which the fluid sample was drawn as a function of theoutput signals.

The Rules comprise a set of logical statements: IF/THEN/ELSE, AND, andOR. Evaluating a logical statements will return a true or false result.The logical statements are evaluated based on data that are input intothe computer controller 28 by the end user, predetermined operatingdata, as well as the test result data generated by FTIR assembly 24 andOES assembly 26.

The expert system includes memory for storing information regardingtested fluid samples. For each sample, a corresponding data structurestored in memory may contain the following pieces of informationassociated therewith: system type (i.e., the type of equipment selectedfrom an equipment list by the end user, such as gasoline engine, dieselengine, and the like); make/model, engine size, time on unit (hours ormiles), time on oil (i.e., since last change), oil sump capacity, aswell as a variety of other pieces of information. See, for example, FIG.17 showing an output report 174 as well as a variety of input fields(identification, oil brand, oil type, and the like).

Predetermined operating data include a database of numericalconcentration levels of particular constituent elements that trigger arating flag associated with each element for which apparatus 10 has beenprogrammed to detect. The flag may assume several states, namely,following: Normal=“N”, Low Normal=“LN”, Abnormal=“A”, High Normal=“HN”,Excessive=“E”, or Severe “S”. This rating flag, as shown in FIG. 17, ifapplicable, may be printed out next to the wear metal.

Referring now to FIG. 16, the basic operation of the expert softwaresystem will now be set forth in detail.

In step 160, the program (“expert system”) executing on controller 28defines parameters for each oil type that the end user selects from theoil type pick list. For example, for a particular oil type, high and lowlimits for viscosity @100c will be set.

In step 162, the unit type parameter is set to “GS”, “MDS”, “MGS”,“MGR”, “DS”, “RRC”, “RRD”, “MT”, “AT”etc. based on the system type thatwas selected by the end user from the equipment selection list. Forexample only, and without limitation, “GS” stands for gasoline engine;“MDS” stands for marine diesel; “MGS” stands for marine gasoline; “MGR”stands for marine gear; “DS” stands for diesel engine; “RRC” stands forrailroad compressor; “RRD” stands for railroad diesel; “MT” stands formanual transmission; and, “AT” stands for automatic transmission.

In step 164, the program performs an integrity check of the FTIR testresults to insure the quality of the diagnostic process. For example, ifthe value of soot, H₂O or SYNTH are above a certain cutoff point, thenthe remainder of the FTIR properties will be effectively ignored (andthe printout will replace actual measurements with an “*”).

In step 166, the expert program evaluates a set of rules associated withthe set unit type. The evaluation step evaluates only those rules thatare specifically designed for the selected unit type, as defined in step162 above. For example, if the customer selects gasoline engine as thetype of sample that needs to be tested, then step 162 will set unit typeto “GS”, and thus all rules have the prefix “GS” will be evaluated, inlight of measurement test results.

In step 168, the expert system generates a diagnostic code based on theevaluation of the rules. In a constructed embodiment, the diagnosticcode is a two alphanumeric character code, which is an internalshorthand for a simple, easy to understand block of text provided to theend user on the screen and/or printed report.

In step 170, the diagnostic code is expanded into descriptive text forthe end user, appropriate formatting is done (e.g., replace all negativenumbers with appropriate default values, and all values that exceed apredetermined limit with a greater than sign “>” next to a predeterminednumber, and the like).

In step 172, the test results are output, an example of which is shownin FIG. 17 as report 174.

The Expert System also recognizes that factors other than equipment wearmay vary wear metal concentrations. For example, a Mileage AdjustmentFactor (“MAF”) formula is designed to adjust the alarm limits for theWear Metal Elements based on the Time On Oil. The longer the oil staysin the engine the more wear particles will accumulate.

The Rules, as noted above, are logical statements that are evaluatedduring analysis, and, in a constructed embodiment, may take the form asfollows:

Rules

Diagnostic Code

Condition1

Operand

Condition2

.

.

etc.

Statement if the combination of all conditions are True

Each Rule set (e.g. “RULEDS”) comprises a plurality of rules to beevaluated. Below are examples of various rules included in rule setdesignated “RULEDS” (i.e., diesel).

RuleDS ********************************************************* Rulesthat contain different combination conditions for “OES”    ********************************************************** 1. ‘EVERYTHING IS NORMAL EA, SP, 18 IF Not BKOH AndallNormal(“Al,Cr,Cu,Fe,Pb,Sn”) ANDallNormal(“Si,K,Na,H2O,Fuel,Soot,GLY,V100C,Oxi”) ANDUCase$(CurOilWeight) <> “UNKNOWN” ALL ENGINE WEAR RATES NORMAL. ANALYSISINDICATES PROPER PERFORMANCE OF THE LUBRICANT AND UNIT. SAMPLE APPEARSFREE OF EXTERNAL CONTAMINATION. 2.  FE-ABN AND CR-NOR EG IfgetGrade(“Fe”) <> N And Not (BKOH Or getDiagCode(“ED”) OrgetDiagCode(“EP”) Or getDiagCode(“ER”) Or getDiagCode(“ES”) OrgetDiagCode(“ET”) Or getDiagCode(“EZ”)) CYLINDER, CRANK OR CAM SHAFTWEAR INDICATED.********************************************************* These are MakeSpecific Rules                  ********************************************************** 1.  AL-A &(Cr + Fe) N-N or Engine Make is not Detroit 53, 71,92 EH IfgetGrade(“Al”) <> N And Not(BKOH Or checkDetroit Or getDiagCode(“ER”) OrgetDiagCode(“EP”) Or getDiagCode(“EZ”) Or getDiagCode(“ES”)) PISTON WEARINDICATED. 2.  ‘SI-ABN & [(AL,CR,FE) Non Detroit Eng. OR (SN,CR,FE)Detroit Eng. Model 53,71,92] N-N CD, RQ If Not (BKOH OrgetDiagCode(“BM”) Or getDiagCode(“DG”)) And getGrade(“Si”) = A AndanyNotNormal(“Al,Cr,Fe”) AND (getGrade(“Si”) = A AndanyNotNormal(“Al,Cr,Fe”)) DIRT PRESENT. CHECK FILTER AND AIR INDUCTIONSYSTEM. 3.  [(SN+CR+FE+(CU,PB,AL) N-N]  FOR  DETROIT   53,71,92  OR[(AL+CR+FE+(CU,PB,SN) N-N] ER, AA, RZ If checkDetroit And(allNotNormal(“Sn,Cr,Fe”) And anyNotNormal(“Cu,Pb,Al”)) And Not BKOH ORIf Not (BKOH Or checkDetroit) And (allNotNormal(“Al,Cr,Fe”) AndanyNotNormal(“Cu,Pb,Sn”)) AND If (anyNotNormal(“Al,Cr,Fe”)) AND IfgetDiagCode (“ER”) Or getDiagCode(“TN”) Or getDiagCode(“EB”) OrgetDiagCode(“ES”) Or getDiagCode(“EZ”) And Not(getDiagCode(“CG”) OrgetDiagCode(“T4”)) PISTON, RING, CYLINDER AND BEARING WEAR INDICATED.CHECK FOR POWER LOSS, BLOW-BY, SMOKING, OIL CONSUMPTION, ETC. CHECK FOROIL PRESSURE DROP AND ABNORMAL NOISE.********************************************************* Rules thatcontain different combination conditions for the “FTIR” ********************************************************** 1.  ‘HIGHH2O-SEVERE YK, SC If getGrade(“H2O”) = S And Not getDiagCode(“CS”) ANDIf getRawConc(“H2O”) > 0.5 And Not getDiagCode(“CS”) HEAVY CONCENTRATIONOF WATER PRESENT. CHECK FOR SOURCE OF WATER ENTRY.********************************************************* Rules for HighWear Metals Elements in Break-In/Overhaul     ********************************************************** 1.  ‘AL-ABN(BKOH) JA If (BKOH And getGrade(“Al”) = A And Not(getDiagCode(“EV”) Or(CurVehicleTime = CurOilTime))) Then ALUMINUM LEVEL HIGHER THAN TYPICALFOR BREAK-IN/OVERHAUL PERIOD.********************************************************* QC RULES                        ********************************************************** 1.  ‘REPLACEV100C W/NA IF SOOT > 1.8 48 If getRawConc(“Soot”) > 1.8 setError“V100C” * SOOT LEVEL LIMITS THE ACCURACY OF THE ANALYSIS DATA. 2. ‘REPLACE V100C W/NA IF WATER > 3.0 49 If getRawConc(“H2O”) > 3.0setError “V100C” * HIGH WATER LEVEL LIMITS LIMITS THE ACCURACY OF THEANALYSIS DATA.

It should be appreciated from the foregoing that evaluation of the Rulesresults in an intelligent inference regarding the status of theequipment from which the fluid sample is drawn. Based on the inference,an appropriate message is provided for example: “ALUMINUM LEVEL HIGHERTHAN TYPICAL FOR BREAK-IN/OVERHAUL PERIOD.”

Apparatus 10, under full computer control, performs all datapreprocessing, and data extraction to obtain relevant analysis datapertinent to the specific analyses that are being performed.Calibrations are based on built-in calibration information. The finalsample data are then presented to an expert system, which is used forthe generation of diagnostic statements for the assessment of thecondition of the fluid (oil) and/or the operating equipment. The finalresults are presented on a flat panel display for operator review, andare also available for hard copy generation, archive storage and/orcommunication via modem or to a local network via an Ethernetconnection.

While the present invention was illustrated and described with respectto a preferred embodiment, such description is exemplary only and notlimiting in nature. Other aspects, objects, and advantages of thisinvention may be obtained from the study of the drawings, and thedisclosure. It is well understood by those skilled in the art thatvarious changes and modifications can be made in the invention withoutdeparting from the spirit and scope thereof, which is limited only bythe appended claims. For example, the selection of measurement devicesare not limited to arc emission spectrometers, FTIRs and viscometers. Anapparatus in accordance with the invention may also include, whereappropriate, other forms of absorption spectrometers, such as UV-visiblespectrometers, for composition and color measurements, other forms ofemission spectrometers, such as fluorescence and Raman spectrometers,electrical property measurements, such as resistivity, capacitance andconductivity for rudimentary condition monitoring, laser-based opticalmeasurements, such as composition monitoring and light scatteringdevices, and other physical measurement devices providing diagnosticinformation that can be automated, and can be interpreted meaningfullyby a computer-based expert system.

We claim:
 1. A method of normalizing an intensity of and regularizing asample spectrum of a fluid sample generated by a spectrometer having apair of electrodes, the method comprising the steps of normalizing theintensity by: selecting a background spectral feature from a pluralityof spectral features of a background spectrum that is indicative atleast in part of the composition of the electrodes wherein thebackground spectral feature has an intensity variation characteristic;and transforming the sample spectrum with respect to intensity inaccordance with an intensity of said selected background spectralfeature as indicated in the sample spectrum; the method comprisingregularizing the intensity by: (A) defining a background spectrum havinga plurality of spectral features indicative at least in part of thecomposition of the electrodes; (B) selecting at least a first backgroundspectral feature from said plurality of spectral features wherein thefirst background spectral feature has a predetermined wavelength valueassociated therewith; (C) determining a measured wavelength value of theat least first background spectral feature in the sample spectrum; and(D) translating the sample spectrum with respect to wavelength inaccordance with said predetermined wavelength value, said measuredwavelength value, and a predetermined translation strategy.
 2. Themethod of claim 1 wherein the sample spectrum comprises an array ofvalues representative of wavelengths and spectral intensities associatedtherewith over a spectral range, wherein said plurality of spectralfeatures are defined by corresponding emission lines, and wherein step(B) is performed by the substep of: selecting a plurality of emissionlines from the background spectrum wherein each selected emission linehas a respective predetermined wavelength value associated therewith. 3.The method of claim 2 wherein step (C) is performed by the substeps of:identifying the plurality of selected background emission lines in thearray of values; and, determining a respective measured wavelength valueof the identified emission lines in the array.
 4. The method of claim 3wherein step (D) is performed by the substeps of: determining arespective wavelength offset between the predetermined wavelength valuesand the measured wavelength values; converting the wavelength offsetsinto a composite wavelength offset for the sample spectrum; determininga pixel shift number as a function of the composite wavelength offset;and, shifting the spectral intensities of the array of values by thepixel shift number to thereby regularize the sample spectrum withrespect to wavelength.
 5. The method of claim 1 wherein the fluid samplecomprises one of used lubricating oil and used functional fluid, andstep (A) includes the substeps of: exciting a new sample of said one oflubricating oil and functional fluid corresponding in type and grade tothe used sample to spectroemissive levels to thereby generate radiation;acquiring a background spectrum responsive to the radiation; and,storing the background spectrum for subsequent use.
 6. A method ofnormalizing an intensity of a sample spectrum of a fluid sample by aspectrometer having a pair of electrodes, the method comprising thesteps of: (A) selecting a background spectral feature from a pluralityof spectral features of a background spectrum that is indicative atleast in part of the composition of the electrodes wherein thebackground spectral feature has an intensity variation characteristic;and (B) transforming the sample spectrum with respect to intensity inaccordance with an intensity of said selected background spectralfeature as indicated in the Sample spectrum; the method furthercomprising the step of regularizing the sample spectrum.
 7. The methodof claim 6 wherein the step of regularizing the sample spectrumcomprises translating the sample spectrum with respect to wavelength inaccordance with a first background spectral feature having a knownwavelength selected from a background spectrum having a plurality ofspectral features indicative at least in part of the composition of theelectrodes.
 8. The method of claim 7 wherein the sample spectrum is oneof a lubricating oil sample and a functional fluid sample having one ormore constituent elements, further comprising the steps of: determiningan intensity of a second background spectral feature having an intensityvariation characteristic; determining an intensity of a characteristicemission line associated with at least one of the constituent elements;transforming the constituent element intensity into a concentrationparameter using (i) the intensity of the second background spectralfeature in the sample spectrum, (ii) the intensity of the constituentemission line, and (iii) predetermined data.
 9. The method of claim 6further comprising the step of subtracting a reference spectrum fromsaid sample spectrum.
 10. The method of claim 9 further comprising thestep of adjusting intensity of said reference spectrum before the stepof subtracting.
 11. The method of claim 10 wherein the step of adjustingis performed with reference to a spectral space where there are nosignificant spectral features.
 12. The method of claim 9 wherein saidstep of subtracting is performed on a point-by-point basis.
 13. A methodof normalizing an intensity of a sample spectrum of a fluid sample by aspectrometer having a pair of electrodes, the method comprising thesteps of: (A) selecting a background spectral feature from a pluralityof spectral features of a background spectrum that is indicative atleast in part of the composition of the electrodes wherein thebackground spectral feature has an intensity variation characteristic;and (B) transforming the sample spectrum with respect to intensity inaccordance with an intensity of said selected background spectralfeature as indicated in the sample spectrum; wherein the fluid samplecontains constituents, and wherein step (A) is performed by the substepsof: identifying an emission line associated with at least oneconstituent; selecting a first set of spectral features from theplurality of spectral features of the background spectrum; obtaining apredetermined number of spectra of the fluid sample using the pair ofelectrodes; determining a first intensity variation of said identifiedemission line over said predetermined number of spectra; determining,for each spectral feature in said first set, a respective secondintensity variation over said predetermined number of spectra; selectingspectral features from said first set that have a respective secondintensity variation that is less than said first intensity variation tothereby form a second set of spectral features; selecting one of thespectral features from said second set based on predetermined criteria.14. The method of claim 13 wherein determining a respective secondintensity variation step comprises the substeps of: dividing, for eachone of said predetermined number of spectra, the intensity of theidentified emission line of the constituent by the intensity of therespective background spectral feature in the first set to therebyproduce ratio values; and, calculating said second intensity variationusing said ratio values.
 15. The method of claim 13 wherein step (B)includes the substeps of: measuring the intensity of the backgroundspectral feature in the sample spectrum; and, ratioing at least aportion of the intensity of the sample spectrum by the measuredintensity of the background spectral feature.
 16. The method of claim 15wherein the electrodes comprise silver material and the backgroundspectral feature comprises a 336 nm silver emission line, and themeasured intensity comprises area under a curve associated with the 336nm silver line.
 17. A method of analyzing a sample spectrum of one oflubricating oil sample and a functional fluid sample having one or moreconstituent elements wherein the sample spectrum is generated by aspectrometer having a pair of electrodes, the method comprising thesteps of: (A) translating the sample spectrum with respect to wavelengthin accordance with a first background spectral feature having a knownwavelength selected from a background spectrum having a plurality ofspectral features indicative at least in part of the composition of theelectrodes; (B) determining an intensity of a second background spectralfeature having an intensity variation characteristic; (C) determining anintensity of a characteristic emission line associated with at least oneof the constituent elements; (D) transforming the constituent elementintensity into a concentration parameter using (i) the intensity of thesecond background spectral feature in the sample spectrum, (ii) theintensity of the constituent emission line, and (iii) predetermineddata.
 18. The method of claim 17 wherein step (D) further includes thesubstep of: subtracting a reference spectrum from the sample spectrum.19. The method of claim 17 wherein the sample spectrum comprises ann-row array of values representative of wavelengths and spectralintensities associated therewith over a spectral range where ncorresponds to a number of pixels of an imaging device in thespectrometer, and wherein step (A) is performed by the substeps of:selecting multiple emission lines from the plurality of spectralfeatures of the background spectrum wherein each emission line has apredetermined known, wavelength value; determining a respective measuredwavelength value for the multiple emission lines in the array of values;determining a respective wavelength offset between the predeterminedknown wavelength values and the measured wavelength values, for eachselected emission line; determining a pixel shift number as a functionof the wavelength offsets; and, shifting the spectral intensifies in thearray by the pixel shift number.
 20. The method of claim 19 furtherincluding the steps of: evaluating a plurality of rules in response tothe constituent concentration parameter and producing a plurality ofoutput signals; and, determining a condition of a component of equipmentfrom which the sample was drawn as a function of said output signals.